Major depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations.

This study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples.

We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18–0.34, p = 8.5 × 10−6). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI −0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06–0.08), female sex (beta = 0.160, 95% CI 0.15–0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03–0.07), while neither the depression PGS (beta = 0.004, 95% CI −0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI −0.01 to 0.03) were strongly associated with MDD.

Estimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.

Cross-national studies have found, unexpectedly, that mental disorder prevalence is higher in high-income relative to low-income countries, but few rigorous studies have been conducted in very low-income countries. This study assessed mental disorders in Nepal, employing unique methodological features designed to maximize disorder detection and reporting.

In 2016–2018, 10714 respondents aged 15–59 were interviewed as part of an ongoing panel study, with a response rate of 93%. The World Mental Health version of the Composite International Diagnostic Interview (WMH-CIDI 3.0) measured lifetime and 12-month prevalence of selected anxiety, mood, alcohol use, and impulse control disorders. Lifetime recall was enhanced using a life history calendar.

Lifetime prevalence ranged from 0.3% (95% CI 0.2–0.4) for bipolar disorder to 15.1% (95% CI 14.4–15.7) for major depressive disorder. The 12-month prevalences were low, ranging from 0.2% for panic disorder (95% CI 0.1–0.3) and bipolar disorder (95% CI 0.1–0.2) to 2.7% for depression (95% CI 2.4–3.0). Lifetime disorders were higher among those with less education and in the low-caste ethnic group. Gender differences were pronounced.

Although cultural effects on reporting cannot be ruled out, these low 12-month prevalences are consistent with reduced prevalence of mental disorders in other low-income countries. Identification of sociocultural factors that mediate the lower prevalence of mental disorders in low-income, non-Westernized settings may have implications for understanding disorder etiology and for clinical or policy interventions aimed at facilitating resilience.

Retrospective reports of lifetime experience with mental disorders greatly underestimate the actual experiences of disorder because recall error biases reporting of earlier life symptoms downward. This fundamental obstacle to accurate reporting has many adverse consequences for the study and treatment of mental disorders. Better tools for accurate retrospective reporting of mental disorder symptoms have the potential for broad scientific benefits.

We designed a life history calendar (LHC) to support this task, and randomized more than 1000 individuals to each arm of a retrospective diagnostic interview with and without the LHC. We also conducted a careful validation with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition.

Results demonstrate that—just as with frequent measurement longitudinal studies—use of an LHC in retrospective measurement can more than double reports of lifetime experience of some mental disorders.

The LHC significantly improves retrospective reporting of mental disorders. This tool is practical for application in both large cross-sectional surveys of the general population and clinical intake of new patients.

Although mental disorders are significant predictors of educational attainment throughout the entire educational career, most research on mental disorders among students has focused on the primary and secondary school years.

The World Health Organization World Mental Health Surveys were used to examine the associations of mental disorders with college entry and attrition by comparing college students (n = 1572) and non-students in the same age range (18–22 years; n = 4178), including non-students who recently left college without graduating (n = 702) based on surveys in 21 countries (four low/lower-middle income, five upper-middle-income, one lower-middle or upper-middle at the times of two different surveys, and 11 high income). Lifetime and 12-month prevalence and age-of-onset of DSM-IV anxiety, mood, behavioral and substance disorders were assessed with the Composite International Diagnostic Interview (CIDI).

One-fifth (20.3%) of college students had 12-month DSM-IV/CIDI disorders; 83.1% of these cases had pre-matriculation onsets. Disorders with pre-matriculation onsets were more important than those with post-matriculation onsets in predicting subsequent college attrition, with substance disorders and, among women, major depression the most important such disorders. Only 16.4% of students with 12-month disorders received any 12-month healthcare treatment for their mental disorders.

Mental disorders are common among college students, have onsets that mostly occur prior to college entry, in the case of pre-matriculation disorders are associated with college attrition, and are typically untreated. Detection and effective treatment of these disorders early in the college career might reduce attrition and improve educational and psychosocial functioning.